Joint Learning of Named Entity Recognition and Relation Extraction
Named entities are important to extract relations. Accurate relation classification helps recognize named entities. The paper presents a joint approach of named entity recognition and relation identification. The identified relation is utilized to improve named entity recognition. The method has been applied to identify the names of persons and organizations and five relations between them. The result shows that the joint approach has improved the recall and F-measure of named entities without scarifying the precision. Meanwhile, the recall and F-measure are also improved in the relation extraction.
named entity recognition relation extraction joint learning
Qiuyan Xu Fang Li
Dept. of Computer Science & Engineering Shanghai Jiao Tong University Shanghai, China
国际会议
哈尔滨
英文
1978-1982
2011-12-24（万方平台首次上网日期，不代表论文的发表时间）